Sweet Pepper Seed Inspection Using Image Processing Techniques

Abstract

Since seeds are the foundation of agriculture and the Thai government plans to make Thailand an export hub of seeds under the Asean Economic Community (AEC) 2015, seed quality plays an important role in the seed production. Traditionally, physical attributes of seeds are inspected by human. However this method is very time-consuming and it highly relies on human skills and experience. Thus, in this paper, we focus on seed quality inspection of sweet pepper seeds using image processing techniques. Sweet peppers are very interesting since they have been one of the most important vegetable around the world and they have a variety of vitamins and nutrients. To identify defective sweet pepper seeds, two features used in our proposed algorithm are seed color and seed size. As shown in the results, percent accuracy of abnormal seed color and unaccepted seed size detection are 95.82% and 90.76%, respectively.

Performance and seed quality of several open pollinated chili seed lots

“…The seed size in this study was manually measured using a digital calliper. In the future, it will be possible to measure seed size to determine the quality/purity of seeds/genetics by machine learning more accurately without damaging the [32,[36][37][38][39]. Different letters indicate significant differences between means within columns at Tukey's 5% level of significance The weight of 1000 grains of chili seeds ranges from 3.68 -6.71 g (Table 3).…”

The Role of Thermal and Electrical Energies to Increase the Pepper Quality: A Review

“…Sometimes, size and colour-checking are integrated into one packet of activities. The integration activity is called an image processing technique [50]. Pepper in the form of powder is mainly preferred over whole seed, essential oil, and oleoresins when used as a flavouring agent [51].…”